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of this project. The candidate’s background can be either in in traditional music analysis (with a PhD in musicology, music analysis or music theory) and/or in computational musicology, digital humanities
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recovered, transcribed, and edited within the scope of this project. The candidate’s background can be either in in traditional music analysis (with a PhD in musicology, music analysis or music theory) and/or
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collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be expected to lead the research into innovative ways in which the machine
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. The successful candidate will have the responsibility of developing, in collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be
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the project under the supervision of the PI, with input from a wider project management group and a PPI steering committee. The successful candidate will have a PhD in Psychology, Social Science, Health or a